The plight of humanity: Online impulse shopping in China

Abstract

Online impulse buying (OIB) has drawn increasing scholarly attention across disciplines. The current study aims to examine how motivational factor (Hedonic and utilitarian web browsing), emotional factor (perceived usefulness and perceived ease of use) effect online impulse buying behavior with regard to “Double Eleven” shopping festival. A total of (n = 648) online shoppers were selected for data collection in four cities: Beijing, Tianjin, Nanjing and Shanghai. Interviews were conducted from 60 university students. Structure equation modeling was employed for data analysis. Furthermore, reliability, convergent and discriminant validity analysis was utilized for the results of the structural model. The findings demonstrated that both motivational and emotional factors have a strong and positive influence online impulse buying. Perceived ease of use has less influence on OIB compared to other variables. This study provides a deep insight of e-shoppers toward online impulse behavior in the field of Chinese e-commerce industry that can be generalized to other countries. To the best of our knowledge, this study is first to discover the dynamics of online impulse buying behavior with motivational and emotional predictors with regard to the biggest online shopping festival in China. Implications for scholars and e-tail managers of our study are discussed.

Keywords

“Double eleven” shopping festival e-commerce online impulse buying hedonic web browsing utilitarian web browsing perceived usefulness perceived ease of use

Umair Akram, He is a Ph.D (Marketing) Scholar at School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, China. Before commencing his Doctoral research, he worked as a Lecturer of marketing management at Institute of Business and Management Sciences, UAF, Pakistan. He holds post-graduation in Business Administration specialized in Marketing. He is the author of several publications and international conference proceedings. He is working on different projects of National Natural Science Foundation of China. He is editorial board member of Business and Management studies. His Current areas of interest includes, Impulse Buying Behavior, E-Marketing and Internet Finance.

Hui Peng, is born in Hunan, China on Sep. 11th, 1969. Educational background: Ph.D of Finance, People’s Bank of China, Beijing, China, 1998. She is currently working as a Professor of Finance/Director of Internet Finance Research Center, Beijing University of Posts and Telecommunications, Beijing, China. She was a visiting scholar in University of Michigan, Michigan, U.S.A. 2003–2005, she was post-doctorate researcher in Renmin University, Beijing, China. Current research interest: risk management; E-commerce. Professor Peng is a member of Global Association of Risk Professionals, and a member of International Association of Computer Science and Information Technology.

Muhammad Kaleem Khan, He is a Ph.D Scholar at Beijing University of posts and Telecommunications, Beijing China. Before commencing his Doctoral research, he worked as a Lecturer of finance at COMSATS Institute of Information and Technology (CIIT). He is the author of several publications and International conference proceedings. He holds post-graduation in Business Administration specialized in Finance. His areas of interest include Finance, Crowdfunding, Corporate Governance and E-Commerce.

Sehrish Khan Saddozai, is a Ph.D researcher at Beijing University of Posts and Telecommunications, China in the school of Economics and Management. She received her Post graduation degree in sociology from Bahauddin Zakariya University Multan, Pakistan and also worked as a lecturer in Bahaudin Zakariya University Multan Pakistan. Her research interests are HRM, Talent Management and Employee Psychology.

Zubair Akram, He is a PhD Scholar at School of Management and Economics, Beijing Institute of Technology Beijing, China. Before commencing his doctoral research, he worked as a lecturer. He holds post-graduation in Marketing Management. His area of interest includes Leadership, organizational commitment and consumer psychology.

Misbah Hayat Bhatti, she is a PhD Scholar at School of Management and Economics, Beijing Institute of Technology Beijing, China. Before commencing his doctoral research, she worked as a lecturer Govt. College women University Faisalabad, Pakistan. He holds post-graduation in Human Resources Management. His area of interest includes organizational justice, organizational commitment and employee psychology.

1 Introduction

With the growing field of e-commerce, online shopping trend is becoming popular across the world. China has become the largest e-commerce economy in the world. The number of businesses joining the e-commerce industry has grown rapidly in this context; in order to carry out online shopping business, the number of shops have mushroomed. From the “large” online mall to the “tiny but excellent” Taobao shop, customers have more choices as the online shopping industry intensifies with the growth of style and variety of products in online shops. In this context, the “Double Eleven” online shopping festival has emerged in a clever combination of holiday consumer psychology and consumer price promotion marketing.

Consumers always prefer to buy goods online especially on occasions. Most of the time when they make decisions about online shopping they act impulsively. One click ordering, easy access to products, rich information about products and saving time are all factors that lead to buying impulsively online. There are many factors that influence these impulse buying behaviors. Impulse purchase is explained as compelling, hedonically complex and unplanned buying behavior [49]. With the tremendous growth of e-commerce and rapid development of information technology, online impulse purchasing has become an epidemic. It is also noteworthy that about 40% of all online shoppers’ spending is attributable to online impulse purchasing [31, 54]. Online shopping setting is more encouraging to impulse buying behavior than its offline complement. The online shopping environment liberates consumers from the constraints (e.g. social pressure from the staff, inconvenient store locations, limited operating hours, and time consumption) that they might experience during physical shopping events [16].

According to the CNNIC report in December 2015 China had 688 million netizens, up 39.51 million over the previous year. The internet penetration rate reached 50.3%, up 2.4% points from the end of 2014 (see Fig. 1), The survey result shows that in 2015, the mobile phone was the most popular device used for internet access by new internet users, by 71.5% of them, up by 7.4 percentage points from the end to 2014. Among the new internet users in 2015, 46.1% were under 19, and 46.4% were students, and entertainment and communication were their two biggest reasons to access the internet [8]. Online impulse purchase is defined as an immediate and sudden online transaction with no preexisting shopping intentions [45]. Previous studies reported that unplanned buying account for up to 60% of all purchases [22, 36] and according to [18, 25] 40% to 60% of impulse purchases depending on product category. A number of studies have been done in the offline setting with impulse buying, while little attention focused on online impulse buying. Recently in an online business setting, scholars have studied how to better appeal to impulse shoppers to take advantage of the behavior which has helped brick and mortar retailers flourish for decades [27 , 57]. Irrespective of context, a main purpose in retailing is to increase the attraction to improve sales [5, 25]. Due to the pervasiveness and practical implications of impulse purchasing, retailers have focused significant efforts on facilitating the behavior [12, 27]. This study is not only beneficial for online retailers, but it also has future directions and guidelines for scholars who have studied impulse buying behavior and produced a number of studies in last decade.

In this regard, it is important to comprehend the relative benefits of buying online over offline shopping. Therefore, retailers should be aware of the motivations behind the consumers’ online buying process. Motivations are an essential factor to define the individual’s behavior. They stem unmet needs and represent, through concrete actions, the benefits which people hope to achieve [50]. Two types of motivational factors influence online shopping: utilitarian and hedonic motivations [35]. While making essential consumption decisions, it is reasonable to create a difference between utilitarian and hedonic motives. These motives construct two aspects of attitudes with respect to behavioral acts. Hedonic motivations are related to experiential or emotional aspects which make a pleasurable shopping experience while utilitarian motivation aspects are associated with rational, functional, practical, economic or extrinsic benefits. In this research, we focus on how these two motivations influence online impulse shopping.

In China, the online shopping market has shown great potential due to rapid growth of Chinese netizens and online consumers (see Fig. 1). In order to achieve the competitive, advantage a number of businesses are joining the e-commerce industry. They must grasp consumer needs and try to meet their demands, they should make a marketing strategies (e.g. low price product, augmented services, speedy transaction process, quality of products) to earn profit and attract netizens. In this regard, the “Double Eleven” online shopping festival has an emerging trend. Taobao introduced “Double Eleven” shopping festival on November 11, 2009 on “Singles’ Day.” This online shopping event is most popular among Chinese netizens/e-commerce industry and it is the largest commercial activity. Early 2016, the festival had been successfully held seven times. This event has carried out vast economic benefits, which have increased year by year, reviving the record single-day net buying business amount (see Table 1). Aforesaid studies about online impulse buying behavior have shown the need to identify how online impulse purchases are effected due to this event because to the author’s best knowledge no study has been conducted in this context.

Only a few researchers have studied to examine the “Double Eleven” model successful factors from different perspectives. Liu, [31] reported that this setting can effectively motivate online shoppers to create impulse buying behavior. Yu and Xiao [61] think the “Double Eleven” event uses psychological tactics to mobilize consumer desire to buy by using the curiosity of people in a “single culture.” Jie and Fu [24] found that “Double Eleven” puts a single group as the center of its marketing activities, creating an “eyeball economy” that attracts the public’s attention in order to create wealth. But in the model, itself there are problems, such as Ming [34] pointed out: “Double Eleven” led to unsustainable overdraft consumer spending, and business enterprises will fall into a homogenization of prices.

This study provides a better comprehension about motivational and emotional factors that influence online impulse buying adoption in China with the perspective of “Double Eleven” shopping festival. A little work has been investigated on the relationship between motivational, emotional factors and online impulse buying, but no single study has yet investigated these factors in the context of “Double Eleven” shopping event. The Current study fills this gap by incorporating the conception of motivational factors i.e. Utilitarian and Hedonic, and emotional factors i.e., perceived usefulness (PU) and perceived ease of use (PEOU) on online impulse buying behavior in the context of “Double Eleven” shopping activity.

Aforementioned discussions, the purpose of this manuscript is threefold: (1) to highlight the major findings in study regarding “Double Eleven” shopping festival, (2) to investigate the relationship between online impulse buying and motivational factors (hedonic and utilitarian motivations) with the regard to “Double Eleven” shopping activity (3) to explore the relationship between emotional factors (perceived usefulness and ease of use) and online impulse buying with regard to “Double Eleven” shopping activity. The rest of the manuscript is organized as follows. First, we discuss core concepts of online impulse buying, motivational factors, emotional factors and their relationship, based on their connection we develop the hypotheses and draw research models. Next, we test the hypotheses based on data collection and data analysis. Finally, present the research outcomes, managerial implications and future direction.

2 Literature review and hypotheses building

2.1 Online impulse buying

Akram et al., [1, 2] believe that impulse purchasing is an immediate, unplanned, compelling and sudden purchase behavior while shopping. Consumers usually tend to make immediate and unintended purchases while making online purchases [64]; their intentions when online buying might be related to website complicity and simplicity [58]. In this context, Sharma et al., [51] demonstrated that online buying is driven by low cognitive control or spontaneous behavior and consumers’ emotions. They argued that a consumer’s impulse buying behavior is driven by appealing objects, which influence them to make purchases without considering financial and other factors. Park et al., and Verhagen and van Dolen [44, 54] mentioned that online consumers are more impulsive compared to offline store shoppers. Many consumers tend to overspend due to online transactions because the virtual procedure does not feel like spending money [13]. Online marketing stimuli make buying spontaneous and allow online buyers to be less risk-averse [39]. E-impulse is influenced by many motivational, emotional and other factors such as web site quality, sales promotion, ease of payment.

2.1.1 A taxonomy structure of online impulse buying variables

For the theoretical foundation in online impulse buying studies, S-O-R structure was most commonly utilized because this framework has conventionally providing background in the field of consumer behavior studies. Additionally, many studies regarding online impulse buying behavior have focused on the role of environmental cues in OIBB. Irrespective of their adopted theoretical framework, previous studies about online impulse buying have frequently investigated the association between consumers affective and cognitive reactions, environmental cues, and the resulting behavior, and extensively describe the environmental psychology paradigm which may be reconciled with S-O-R model. Thus, this study used the S-O-R framework to describe the taxonomy of factors in online impulse buying studies. Three major components of S-O-R model.

S _(Stimulus)

O _(Organism)

R _(Response)

2.1.2 Online impulse buying stimulus

A stimulus is a trigger that arouses consumers. Two types of stimulus identified in literature, internal and external stimulus. Internal stimuli were consumer’s characteristics whereas external stimuli were situational, marketing and website stimuli. Website stimuli are indications entrenched in online shopping websites that are audible to consumers and visible [16]. Marketers used marketing cues to attract the consumers to make purchases creating marketing stimuli [62]. Situational stimuli are the environmental and social influences linked with a specific consumption occasion that effect consumers’ impulse buying responses [12]. Additionally, situational factors may decrease or increase consumers’ tendency to buy impulsively. Impulse behavior features are intrinsic/inherent variables of consumers that are associated with their tendency to act impulsively [26, 53].

2.1.3 Online impulse buying organism and response

There are two types of organism, affective and cognitive reactions. Organism refers to consumers’ internal evaluations. Affective reactions are the emotional responses that arise when consumers interact with an environment [52], whereas cognitive reactions are the mental process that occurs when consumers interact with stimuli. They take place when consumers become aware of potential constraints during the online impulse purchase process [43]. The last and third element of S.O.R framework is response. Response is a consumer’s reaction towards online impulse buying behavior stimuli and organisms [4].

2.2 Hedonic and utilitarian

According to the scholars [39, 40] utilitarian and hedonic factor both influence impulse purchasing. Impulse purchasing and different kinds of browsing are effortless feelings [51]. Online shoppers are motivated by searching due to the benefits of entertainment, uniqueness and fun [19]. For specific products, online impulse buying occurs due to emotional and hedonic browsing [23]. Internet facilitates browsing the online merchandise for informational purpose (utilitarian) and recreational (hedonic) browsing [39]. Consumers usually act impulsively when they are making online decisions due to easy buying e.g., one click order, absence of delivery efforts and easy access to products [54]. Park et al., [44] confirmed that utilitarian and hedonic browsing have a relationship with impulsiveness in the context of online buying of apparel products. Additionally, Gohary and Hanzaee [17] demonstrated that the effect of hedonic and utilitarian browsing on impulse behavior points towards the importance of hedonic and utilitarian browsing for impulse purchasing over the internet [28, 54]. Finally, Rezaei et al., [46] confirmed that utilitarian and hedonic browsing positively influence online impulse buying. Based on above studies, the following hypotheses regarding the relationship between motivational factors and online impulse buying are derived:

Hedonic web browsing positively relate with online impulse buying in the context of “Double Eleven” shopping events.

Utilitarian web browsing positively relate with online impulse buying in the context of “Double Eleven” shopping events.

2.3 Perceived usefulness

The degree to which the online shopper believes that their shopping efficiency will be enhanced by utilizing a specific website [43]. In the context of technology acceptance model (TAM), several studies have described that perceived usefulness has a significant relationship with specific behaviors toward adopting many information systems e.g., hedonic information system [59]. With regard to impulse purchase on web site/web store, hedonic information system is a pleasured information system for the enjoyment of online shoppers. According to the Chea & Luo [10] perceived usefulness about product information search on a website is considered an important precursor towards consumers online buying behavior. From a psychological perspective, early studies have generally indicated that the cognitive state of an individual to the exposure of an external stimuli such as PU, when inter-playing with the affective state to strengthen or weaken it, is possibly related to a consumer’s online impulse buying behavior [30]. Based on aforementioned studies about PU and OIB we hypothesized that:

Perceived usefulness positively related with online impulse buying with regard to Double Eleven online shopping festival.

Perceived usefulness moderate the relationship between hedonic web browsing and online impulse buying, such that the relationship is stronger when the degree of PU is high and the relationship is weakening when the degree of PU is low.

2.4 Perceived ease of use

The extent to which online shoppers believe that using a specific website for purchasing would be free from constraints [54]. Perceived ease of use is a significant influence on online shoppers. Positive assessment of usability with perceived ease of use had a positive influence on positive emotions and negative influence on negative emotions [15]. Many scholars indicated that factors effect impulse buying: when online users are experiencing positive affect, they are more likely to be involved in this context. Additionally, positive feeling of emotions by online shoppers enhance the impulse buying and overspending [55]. Therefore, we hypothesized:

Perceived ease of use positively related with online impulse buying with regard to “Double Eleven” shopping festival.

\begin{matrix} Mathematical Model : OIB = β_{0} + β_{1} (HWB) \\ + β_{2} (UWB) + β_{3} (PU) + β_{4} (PEOU) + ɛ \end{matrix}

3 Research methods

The aim of this study is to find the motivational factors effect on OIBB on “Double Eleven” shopping festival. Data was collected from four different cities: Beijing, Shanghai, Nanjing, and Tianjin. The survey was conducted on the “Double Eleven” shopping festival date on the 11th of November 2016. Convenience sampling method was utilized to collect the large data. We divided our methodology into two parts, part A (^study one “Quantitative method e.g., data collected through paper questionnaire”) and Part B (^study two “Qualitative method e.g., data collected through personal interview”). In study two we took half of the respondents are same as taken in study one. Rest of the participants we took in study two, those were not belonging to study one participants.

3.1 Questionnaire, ^{(Study one)}

Paper questionnaire and online survey techniques were used for data collection. Initially, a questionnaire was developed/adapt in English and subsequently translated into a Chinese version then back into English for accuracy. Services of Chinese language experts and translators were employed to translate the questionnaire into Chinese. Translation and back translation was validated by the International Chinese Training Center, Beijing. The first part of the questionnaire was designed to ensure the respondents have online buying experience on “Double Eleven” shopping festival and in order to get information related with respondents’ characteristics. The second section was designed to examine the relationship among online impulse buying behavior, hedonic and utilitarian motivations. Pilot tests were utilized (n = 60). Additionally, a total of 700 questionnaires were distributed among online shoppers and receive back 676 and (n = 648) were valid for the data analysis with a response rate of 92.57%. Small gifts (ball points and note books) were provided to the respondents in order to motivate and seduce their patience, which cost about 6 RMB ($0.70).

3.2 Measures of independent, dependent and moderator variables

Perceived usefulness scale, adopted from [38, 63], to measure the 4 items PU. In order to measure the 4 items scale perceived ease of use adopted from [56]. Five items were adapted from [54] to measure the online impulse buying behavior e.g., my purchases were spontaneous. In order to measure the utilitarian web browsing, five items were adopted from Park et al., [44] e.g., I browse to buy items with better price and quality, and to measure the hedonic web browsing four items were adopted from Park et al., [44] e.g., while web browsing I am able to forget my problems and to feel relaxed. Rezaei et al., [46] also used these three instruments in his study (see Appendix A for measures).

3.3 Interview, ^{(Study two)}

The current study has selected online impulse shoppers who have participated in the online “Double Eleven” shopping activity. By using qualitative approach, Face-to-Face interviews were conducted with 60 university students. Student respondents were appropriate because young consumers are more involved in online shopping. We selected the respondents for interview who already had experience in “Double Eleven” shopping event. Each interview took 10 minutes & semi-structured questions were asked, nonstructural questions were designed for further study of answers to those structural questions. In order to persuade the participants, candies and free drinks were provided which cost about 6 RMB. The main purpose of conducting the interview for this study is to identify the factors and problems associated with OIB not included in the structured questionnaire part. The second purpose of collecting data through interview is to find the major problems regarding online impulse buying on “Double Eleven” shopping festival.

4 Results and hypotheses testing

Table 2 reports the demographic characteristics of the respondents. Total 700 questionnaires were distributed, out of 700, 648 respondents were found who had online shopping experience. Demographics show that there are a higher number of female respondents (67%) compared to males (43%). Maximum respondents were 25–31 years of age (39.6% of total respondents). Finally, from an occupational characteristic, students, business owners and employee level job in a sample of primary employment, respectively amounted for 52.8%, 9.8%, 19.6% and 09.2% individuals having managerial jobs. For further detail see Table 2.

$\begin{matrix} Kaiser - Meyer - Olkin (KMO) \\ = {KMO}_{j} = \frac{\sum_{i \neq j} r_{ij}^{2}}{\sum_{i \neq j} r_{ij}^{2} + \sum_{n \neq j} u_{ij}^{2}} \end{matrix}$

$\begin{matrix} ^{b} AVE : \\ = {(\sum_{i = 1}^{k} λ_{i})}^{2} / [{(\sum_{i = 1}^{k} λ_{i})}^{2} + \sum_{i = 1}^{k} (1 - λ_{i})^{2}] \end{matrix}$

$\begin{matrix} ^{a} CR, Measured with the Joreskog Rho \\ = \sum_{i = 1}^{k} λ_{i}^{2} / [\sum_{i = 1}^{k} λ_{i}^{2} + \sum_{i = 1}^{k} (1 - λ_{i}^{2})] \end{matrix}$

4.1 Missing values treatment

It is important to comprehend missing values in order to manage the data. Missing data is an inescapable issue in surveys [32], it may be creating issues in multivariate data analysis. Missing values in data set is a big challenge for social science scholars like information system, human resource management and marketing areas. Many techniques can be performed for the treatment of missing values but multiple imputations are considered effectively [46, 47]. We identified six missing values in current data set. In order to handle missing values and impute missing values effectively by using SPSS, expectation maximization algorithm (EMA) was utilized [32, 46]. For the missing value treatment, little’s missing completely at random MCAR which is chi-square χ ² test for missing completely at random “Little’s MCAR test: χ ² =334.270, df = 332, significance level = 0.444. Therefore, expectation maximization algorithm was employed to impute missing data.

4.2 Multicollinearity issue

Multicollinearity is also called collinearity, when performing a regression model, then this problem can be examined. It refers to predictors that are correlated with other predictors in the model. Before examining the structure model, multicollinearity issues were assessed through variance inflation factor (VIF) produced by SPSS 21 version. The results of VIFs indicated the value of 2.21 for online impulse buying, 1.88 for utilitarian web browsing, 1.43 for hedonic web browsing, for perceived usefulness 2.33, and for perceived ease of use 1.21 variable, all stated values are lower than the threshold value 10 [14]. Therefore, the results show no serious problem of multicollinearity in our study. Furthermore, before factor analysis Kaiser-Meyer-Olkin (KMO) test was assessed for the sampling adequacy which shows KMO value 0.886. KMO value 0.886 should be greater then benchmark value 0.50 [20].

4.3 Common method variance and non-response bias

Common method variance (CMV) and non-response bias used to survey research were investigated before performed structure model analysis. CMV is a major issue in qualitative research and survey related reports and it happens when scholars collect the data from a single source [3]. Therefore, in this study various variables were used for the many relationship constructs, such as precursors of perceived usefulness (independent variable) and PU (moderator variable). There are two solutions to minimize CMV problem i.e., statistical control and designing procedure [48]. The current study found CMV problem at the stage of the questionnaire design and utilizing the very famous statistical method, Harman’s single factor test [42]. Table 5 demonstrated that no single factor extracted variance accounted for <50%. OIB is first factor with 29% of variance accounted. In this regard, we found that CMV is not a problem in this manuscript.

4.4 Structure model results

To examine the structure model confirmatory factor analysis (CFA) was used to test the hypothesis and measurement model by using AMOS 21 version. The results indicated that satisfactory fit (CMIN/DF: 2.333; p < 0.000; GFI = 0.912; CFI = 0.899; AGFI = 0.92; RMSEA = 0.034). All values of CFA analysis were acceptable and meet the threshold values (see Fig. 3). Reliability and Validity test were performed in the model. Convergent validity was employed by using three parameters i.e., (1) χ ² factor loading <0.70 with statistical significance (2) composite reliability (CR) larger then 0.80. (3) Average variance extraction (AVE) higher then 0.50 [20]. Table 3 indicated that all values of factor loading are greater than 0.70, in addition, all constructs show the high level of reliability internal consistency CR and Cronbach’s alpha values ranges from 0.80 to 0.96. The value of AVE is greater then the benchmark value 0.50. Thus, we attained the good level of convergent validity and reliability. Table 4 reports all statistical values of mean, standard deviation and discriminant validity. We used Hair’s criterion to evaluate the discriminant validity which directs square root to average variance extraction AVE for all constructs should be higher than it correlations [20]. Furthermore, Table 4 shows the values of correlations. Among all values of correlation, no higher correlations were found (r > 0.70). All variables are positively correlated with each other i.e., online impulse buying positively related with hedonic web browsing (r = 0.45, p < 0.001_OIB _& HWB^,positive), utilitarian web browsing (r = 0.34, p < 0.001_OIB _& UWB^,positive), PU (r = 0.42, p < 0.01_PU _& OIB^, ^positive) and also OIB positively relate with PEOU (r = 0.34, p < 0.01_PEOU _& OIB^, ^positive). Discriminant validity among all variables were confirmed based upon Hair’s criterion (see Table 3).

Table 6 depicts the results of path coefficients (β) which indicates the hypothesized association among the constructs. Figure 2 represents the results of structure model. H1 that proposes there is a positive relationship between hedonic web browsing and online impulse buying was approved with path coefficient (β) 0.412, t-statistics 21.02 and standard error 0.012. Results demonstrated that hedonic web browsing positive and significantly influences online impulse buying on “Double Eleven” shopping festival. H2 proposed that utilitarian web browsing positively influence online impulse buying (utilitarian web browsing ⟶ online impulse buying) with coefficient (β) of 0.652, standard error of 0.101 and the value of t-statistics 15.32. H2 was also supported. H3 demonstrated that PU positively related with OIB with statistics coefficient (β) 0.325, t-statistics 13.32 and standard error 0.077 which indicated that results of H3 strongly supported. Finally, H5 also supported that PEOU positively influence on OIB with results of path coefficient (β) 0.217, t-statistics 3.23 and standard error 0.031. Furthermore, Table 6 indicates the values of R² for the relationships of constructs. The R² value for (HWB⟶OIB) 0.622, for (UWB⟶OIB) 0.411, for (PU⟶OIB) 0.520, and for (PEOU⟶OIB) 0.256, which means 62.2% change in online impulse buying due to hedonic web browsing while 41.1% change in online impulse buying due to utilitarian web browsing. Hedonic web browsing strongly influences online impulse buying more than utilitarian web browsing. The findings confirm that HWB, UWB, PU and PEOU strongly influence online impulse buying.

Table 7 indicated the results of moderating effect of PU. Hierarchical regression analysis was employed to test the moderation effect of PU. Current model variables were entered in the following order: hedonic web browsing, perceived usefulness and hedonic web browsing × perceived usefulness. Table 7 showed the outcomes of HRA for the main and interaction effects of online impulse buying. The last column shows the significant R2 change moderating effect of the moderator (PU) [33]. The results of main effects are describing above discussions and also show in Table 4. The interaction effect between hedonic web browsing and perceived usefulness (β = 0.865_HWB *PU) on online impulse buying were significant (ΔR² = 0.032_HWB *PU). PU moderate the relationship between hedonic web browsing and online impulse buying. H4 was supported (see Table 7 and Appendix B).

4.5 Results and discussions ^{(Study two)}

The major aim of study two is to investigate the problems regarding “Double Eleven” online shopping events and to grasp such factors’ influence on online impulse buying behavior that we have not addressed in study one. Regarding the investigation of the issue of universality, the most serious problems perceived by consumers as well as consumers participating in the “Double Eleven” had tremendous impact. According to the interview results, the current severity of the top issues were false promotions, businesses creating gimmicks to attract customers and insufficient supply, false propaganda, payment difficulties, slow delivery and slow logistics. The first three issues related with violation of consumers’ interests and the other three influenced consumers’ online shopping.

False promotion is considered a major problem with 38% of consumers ranking it first (see Fig. 4). It is inconstant with promotional discounts that consumers actually. False promotion is inconsistent with promotional dis- counts that consumers actually. False promotion takes many forms, but is difficult for consumers to identify in its high degree of concealment. For example, consumers say the most common problem is that the virtual business raises are original price and then cuts it in half, creating a huge discount illusion for consumers. In addition, the “Double Eleven” slogan is displayed in many shops—“half of the audience”—but when consumers come into the store to buy the product, they found that only a part of the product is half-price, half the audience is not propaganda. More subtly, some businesses in the back half of the audience add the little word “from” and playing a word game with consumers. In addition, businesses are still offering “full one hundred to send one hundred,” “one hundred flowers as two” and coupon redemption activity moves from the mind. While consumers reached Fanquan standards after the publicity they will get the amount of coupons, but these coupons are had extremely poor conditions for use. These are just a few of the most common forms of false promotion; in practice, there are many other ways. It is difficult to investigate its causes because of a lack of rules and regulations and scarce supervision.

The second largest problem is false propaganda with 20%. Often during the “Double Eleven” event the physical and picture text descriptions do not match or there is no in-kind match. In order to attract more consumers, businesses will exaggerate the advantages of commodities (such as using flashing characters, large fonts, etc.,) to demonstrate merits and avoid shortcomings by not mentioning the product. This results in consumers not fully comprehending the true product situation. Regarding the current status of Taobao, we found the main reason for problems is that online shopping platform has a false evaluation of supervision and lacks effective punitive measures. Although Taobao put “consistent description” as one of the indicators evaluating its business reputation and service levels, and the score comes mainly from consumers, it shows a lack of unified impartial evaluation. And it is difficult to determine the punishment for this issue, with false propaganda determining the lack of standards, leading Taobao to various provisions against false propaganda that just stay at the institutional level and are difficult to be effectively implemented. Likewise, it’s false propaganda when businesses create a gimmick to attract customers but there is a supply shortage, the problem is mainly about the business’s purposeful lack of supply. This issue in the “Double Eleven” event is very common. For example, in order to attract customers, “Double Eleven” launched many shops, such as mobile phones for 10 yuan, huge discounts, and other discount promotions. Many involved in buying activity reflect that a lot of low discount merchandise on sale often sold out within 1 min, right off the shelf.

In the end, customers started to wonder the real reason that lead to a 1-min-sold-out. Is it because of the product’s popularity, or just because the seller intentionally had a supply shortage? In addition, consumers reflect, even after having completed payment, that the merchant may notify them that the product cannot be shipped due to a lack of inventory. This is against the interests of consumers. The problem with the current generation of online shopping platform is that there is a lack of rules and regulations related to such issues. Further, it is difficult to identify such problems and define the characteristics of this problem. In the end, for super- cheap goods, is it illegal that businesses were not prepared with enough inventory? What should the punishment be for this kind of illegal business? When they oversell commodity how should consumers be compensated for their time and effort? These questions are worthy of consideration by the relevant departments.

As for the issue of consumer rights violations, combined with empirical results, we found that solving this problem starts with the following aspects. First, businesses should have an established and consumer-centric sense of integrity, provide incentives for consumers, and resolutely put an end to consumer fraud. Second, online shopping platforms such as Taobao should accelerate the construction of merchant credit evaluation system to solve the problem of asymmetric information shopping. For low credibility, false promotion, or false propaganda, outlets can publish notices criticizing the entire site or even set up a special logo to warn consumers to be cautious of shopping with these merchants. Third, governance should be improved and false propaganda and false promotional issues related to systems made explicit for consumer fraud judgment standards, methods of supervision, punishment, and compensation methods. The existing supervision and punishment for violations of a “zero tolerance” attitude should be increased. Emphasis should be placed on the enforceability of the relevant provisions to effectively address such issues as the focus and the ultimate purpose.

Payment difficulties refer to the need to continue payments after consumers in the “Double Eleven” wait for a long time, recurring payments situation fails, or the page cannot be opened. Alipay, the main payment method on Taobao.com, experienced a lot of challenges from the midnight of “Double Eleven”. Analyzing the causes of the problems, we found that in addition to the payment processing provider itself limiting payment levels, relevant agencies paid suppliers for a lower degree of attention to the problems related to the lack of response measures. While Taobao and T-mall used Alipay to complete transactions in the “Double Eleven” event, consumers still need to be paid through port into the net banking system treasure provided the money is transferred to Alipay, which relates to the capacity of the online banking system itself. This is not a huge amount to pay, the existing level of hardware can satisfy payment demand on weekdays, so banks must upgrade their system, and perform a low technical capacity expansion initiative. When the resulting “Double Eleven” traffic peaks and the online paying banking system is paralyzed, consumers cannot successfully complete payment.

Slow delivery means that a single complete payment from the consumer to the merchant to the parcel delivery company takes a long time. The problem mentioned plus the issue of logistics behind the slow delivery of goods will increase the time for consumers and the impact of the actual net consumer’s shopping experience. The problem is more common during the “Double Eleven” and deserves some attention.

Through interviews, we learned that delivery businesses need to go through the steps of the print order, sorting products, verification packing, carrying out extra details for express orders, delivering packages, and so on. However, due to the surge in “Double Eleven” orders, the workload of businesses grows exponentially, resulting in prolonged delivery time. In the interview, the number of businesses that have a small sorting staff, cannot automatically print delivery orders (such as the need for a single shop staff member to fill orders by hand, one by one), couriers pick up slowly, leading to slower business delivery problems.

Slow delivery in “Double Eleven” is prevalent, and related issues such as “ware- house explosion,” etc., in the annual period will be subject to much media’s attention. According to the survey, many consumers worry about the slow logistics because they will not participate again in “Double Eleven” activities. Specifically, the problem is from the merchant shipping to the customer, who waits a long time to receive the goods.

To solve the above problems affecting consumers in the “Double Eleven” shopping experience, first, logistics providers, payment providers, and businesses should improve their ability to cope with the surge of orders processed during the “Double Eleven” trading volume, by, increasing personnel and accelerating information systems and hardware updates. Second, Taobao, JD and other sites should introduce appropriate assessment and incentives. On the one hand, the rules and regulations limit the latest delivery time; however, on the other hand awards result in good business (e.g., businesses with fast delivery are granted a special logo, and so on). Third, businesses should effectively establish service awareness and put the interests of consumers first. Satisfaction with the “Double Eleven” long-term development is closely linked to the customer.

5 Discussions and conclusion

For 7 years, the promotional activities of “Double Eleven” online shopping festival have become one of the most popular festivals in online shopping. Also, the transaction amounts on this one day have rapidly grown and keep setting new records. The current study aims to inspect the relationship between motivational, emotional factors and online impulse shopping. With a remarkable growth of Chinese internet users and tremendous penetration rate of internet (see Fig. 1), web browsing motivation and emotional factors are considered an essential part of online shoppers’ experience. The current study provides important insights of online impulse behavior based on web browsing motivations i.e., Hedonic and Utilitarian and emotional factors i.e., PU and PEOU for e-tailers to develop their e-business strategies especially during big events like “Double Eleven.” This study investigates online impulse buying shoppers towards “Double Eleven” e-shopping festival and examines whether hedonic and utilitarian web browsing have any impact on it. This manuscript contributes to existing studies regarding online impulse buying behavior by using exogenous constructs i.e., perceived usefulness and perceived ease of use and hedonic and utilitarian web browsing. With the remarkable growth of online business, “Double Eleven” has turned out not only a festival to celebrate, but also the most popular and highest sales volume festival in online shopping. This study provides a significant insight of motivational and emotional factors which influence online impulse buying behavior. In China, e-commerce companies are facing the high rivalry environment and they need to make innovative e-business strategies in order to increase online impulse buying, making the results of this paper useful.

The results of this study demonstrated that hedonic and utilitarian web browsing both influence online impulse buying behavior on “Double Eleven” shopping festival. The findings also support a broadened theory of impulse purchase behavior [7], which recommends that web browsing motivation is a key to enhance online impulse purchases for apparel from both hedonic and utilitarian perspectives. Inclination with the findings of this study Kim and Eastim [28] argued that there is a huge difference between hedonic and web browsing behavior in online shopping. With the perspective of utilitarian value, consumers are focused towards completing consumption purposes [6 , 41] while hedonic value, consumers are more attentive on entertainment, emotional and fun when dealing with online browsing [9, 29]. Park et al., [44] found that hedonic web browsing positively influences OIB whereas utilitarian web browsing negatively influenced online impulse buying. In an online shopping context, this evidence supports the hedonic nature of online impulse behavior [5, 44]. Spontaneous shopping behavior can be influenced by hedonic shopping characteristics, while utilitarian shopping characteristics do not influence unplanned shopping behavior [37] for instance, products purchased for functional purposes have a different level than products bought for pleasure [37]. In line with the findings of our study Rezaei et al., 46 found that utilitarian and hedonic both have positive influences on online impulse buying behavior.

Perceived usefulness and perceived ease of use are the important antecedents of the online impulse buying behavior. The current study found that PU strongly influenced OIB. Most recent studies, with regard to technology use, PU is significantly influenced by website design. This demonstrated that user-friendly web design is most important as antecedent for further using the website in enhancing consumers online shopping productivity. PU focuses on the cognitive state in an online consumers’ mind when they interact with the stimulus of a web store. With the significant growth of netizens, consumers comprehend the importance of usefulness of an e-store in searching for appropriate products or services by providing effective navigation. In line with the results of our study Wu et al., 58 argued that PU has a positive relationship with OIB. PU plays a moderator role in enhancing the impulse purchases through the antecedent of hedonic web browsing. Although, PU has a direct effect on OIB, if we used PU as a moderator the relationship becomes stronger than the direct effect on online impulse buying. E-tailer should design user-friendly web sites in order to increase the impulse shopping. Furthermore, Xiang et al., [60] found that PU significantly influences the urge to buy impulsively by using the mediating role of perceived shopping enjoyment. Surprisingly, our findings show that PU strongly influence OIB compared to the perceived ease of use, although PEOU has an impact on OIB.

E-tailers should make successful strategies by focusing on hedonic and utilitarian web browsing motives for e-shoppers by ensuring in a professional manner, for instance; easy purchase process, good selection of variety, elegance and security of the web site. All of these factors lead to online impulse shopper. This manuscript has some important practical implications toward OIB on “Double Eleven” shopping activity. This study’s findings will help the e-tail managers and web hosts associated with online selling to exploit exogenous factors HEB and UWB to enhance their impulse sales through web traffic. Utilitarian and hedonic web browsing play a significant role motivating e-shoppers to buy impulsively especially on “Double Eleven” event. Specifically, in order to achieve the aims, online retailers need to focus on user-friendly interface design to motivate the online impulse buyers in evolving their own process conveniently and easily regarding product searching. The user-friendly interface characteristics boost up consumers’ web skills of using website or increase computer self-efficiency. In China, there is rapid growth towards netizens and the penetration rate of internet users, now every individual prefers buying online. The outcomes of this study will be useful for two e-tail big players in China (i.e., www.jd.com and www.taobao.com) as well as small e-tail businesses. Therefore, marketers should focus on these strategies in order to increase the impulse buying behavior which is a major contribution in the field of e-commerce retailing and marketing.

5.1 Limitations and future directions

Despite all the strengths and potential contributions of the study some limitations should be considered. First, in this study we collect data from four cities of china and only focus on “Double Eleven” shopping festival. It is important to examine the replicability of current study in different e-tail cultural environment and results can be enhanced by expanding the study sample and incorporating more festivals that are found to increase online sales. The majority of samples were women creating a potential gender bias. Moreover, this manuscript has considered only two motivational factors i.e., UWB and HWB, and two emotional factors i.e., PU and PEOU, future scholars may use other factors related to web site personality, psychological and outcomes could be used to improve other type of e-commerce web sites. Pre-and post-purchase behavior with regard to “Double Eleven” shopping festival may also be analyzed by future researchers. Future research should have considered social communities such as Facebook, Twitter and Wechat towards online impulse buying behavior. How have online impulse consumers been influenced through these social communities? Future studies are suggested to add more moderator’s and mediator’s variables. Finally, future studies are recommended to investigate the gender effect on online impulse buying.

Footnotes

Appendix A: Questionnaire

Online impulse buying behavior (OIB)^{(VerhagenandvanDolen, 2011)}

OIB1 My purchase was spontaneous

OIB2 MY purchase was unplanned

OIB3 I did not intend to do this purchase before this shopping trip

OIB4 Before visiting the site, I did not have the intention to do this purchase

OIB5 I could not resist doing this purchase

Perceived Usefulness (PU)^{(Luoet al . ,2012 ;Kofaris2001)}

PU1 Using shopping websites enables me to find the products easily I am looking for

PU2 Using shopping websites enables me to access a lot of products information

PU3 Product information on shopping websites is clear and understandable

PU4 Using shopping websites enables me to accomplish transactions quickly

Perceived ease of use (PEOU)^{(VanderHeijdenandVerhagen,2004}_Modified)

PEOU1 I find this site is easy to navigate

PEOU2 This website has organized layout

PEOU3 It is easy to use shopping through website

PEOU4 I find it is easy to learn how to use this site

Hedonic web browsing (HWB)^{(Parketal . ,2012)}

HWB1 While web browsing, I am able to forget my problems and to feel relaxed

HWB2 During web browsing, I am very excited, like playing

HWB3 I enjoy web browsing enough to forget a time out

HWB4 I look around at items on the internet just for fun

Utilitarian web browsing (UWB)^{(Parket al . ,2012)}

I browse to buy better items in price or quality

I browse the shopping web sites to gather information about product

I look around the shopping web sites to comparison shop

I browse for efficient shopping online

Appendix B: Moderation graph

Notes:

JD.com (online shopping website) https://www.jd.com/

Taobao.com (online shopping website) http://www.taobao.com/

Alipay: Third party payment app. https://www.alipay.com/

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The plight of humanity: Online impulse shopping in China

Abstract

Keywords

1 Introduction

2 Literature review and hypotheses building

2.1 Online impulse buying

2.1.1 A taxonomy structure of online impulse buying variables

2.1.2 Online impulse buying stimulus

2.1.3 Online impulse buying organism and response

2.2 Hedonic and utilitarian

2.3 Perceived usefulness

2.4 Perceived ease of use

3 Research methods

3.1 Questionnaire, (Study one)

3.2 Measures of independent, dependent and moderator variables

3.3 Interview, (Study two)

4 Results and hypotheses testing

4.1 Missing values treatment

4.2 Multicollinearity issue

4.3 Common method variance and non-response bias

4.4 Structure model results

4.5 Results and discussions (Study two)

5 Discussions and conclusion

5.1 Limitations and future directions

Footnotes

Appendix A: Questionnaire

Appendix B: Moderation graph

References

3.1 Questionnaire, ^{(Study one)}

3.3 Interview, ^{(Study two)}

4.5 Results and discussions ^{(Study two)}